st: -xtlogit- vs -xtmelogit- and predicted random effects

I have a random effects logit model which I would like to bootstrap in order
to get confidence intervals on the random effect terms. The model has a single
random intercept, and I can estimate it two different ways:
xtset groupid
xtlogit depvar indvar1 indvar2
or
xtmelogit depvar indvar1 indvar2 || groupid:
These two models give nearly identical results, which is good, but while the
first model takes 6 minutes to run, the second takes 123 minutes (!). Since I
am bootstrapping 1000 samples, only -xtlogit- is practical.
However, despite StataCorp's assurance 4 years ago that it would look into
providing predicted random effects after estimation using -xtlogit-:
http://www.stata.com/statalist/archive/2007-03/msg00135.html
this feature is still not available. My questions:
1) I cannot find an estimation option for -xtmelogit- to match the adaptive
quadrature of -xtlogit-, which would presumably speed it up. Is there one
that I am missing?
2) Or, has someone else looked under the hood of -xtlogit-, as it were, and
written some code for getting the predicted random effects?
3) This is for StataCorp: any progress on adding this postestimation option
to -xtlogit-, per the above posting?
Much to my chagrin - this was for a revise and resubmit on a manuscript, so we had
a very short time to work - I gave this problem to a SAS-using colleague, who ran
it in GLIMMIX in the course of day. GLIMMIX uses pseudo ML, which I know doesn't do as
good a job of estimating the random effect terms, but in a pinch one has to do what
one can - however, I would be very pleased to have a Stata solution (that does not
take 3 months to run).
thanks,
Jeph
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